Climate change may interact with nitrogen fertilizer management leading to different ammonia loss in China's croplands. (12th September 2021)
- Record Type:
- Journal Article
- Title:
- Climate change may interact with nitrogen fertilizer management leading to different ammonia loss in China's croplands. (12th September 2021)
- Main Title:
- Climate change may interact with nitrogen fertilizer management leading to different ammonia loss in China's croplands
- Authors:
- Xu, Xiangrui
Ouyang, Xiao
Gu, Yining
Cheng, Kun
Smith, Pete
Sun, Jianfei
Li, Yunpeng
Pan, Genxing - Abstract:
- Abstract: Despite research into the response of ammonia (NH3 ) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH3 models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi‐layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R 2 of 0.76 and the lowest RMSE of 0.82 kg NH3 ‐N ha − 1, showing the best simulation capability. Results of model importance indicated that NH3 volatilization was mainly controlled by total input of N fertilizer, followed by meteorological factors, human managements and soil characteristics. The NH3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH3 ‐N. By 2050, NH3 volatilization will increase by 23.1−32.0% under different climate change scenarios (Representative Concentration Pathways, RCPs), and climate change will have the greatest impact on NH3 volatilization in the Yangtze river agro‐region of China due to high warming effects. However, the potential increase in NH3 volatilization under future climate change can be mitigated by 26.1−47.5% through various N fertilizer management optimization options. Abstract : A nonlinear model was established to predict NH3Abstract: Despite research into the response of ammonia (NH3 ) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH3 models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi‐layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R 2 of 0.76 and the lowest RMSE of 0.82 kg NH3 ‐N ha − 1, showing the best simulation capability. Results of model importance indicated that NH3 volatilization was mainly controlled by total input of N fertilizer, followed by meteorological factors, human managements and soil characteristics. The NH3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH3 ‐N. By 2050, NH3 volatilization will increase by 23.1−32.0% under different climate change scenarios (Representative Concentration Pathways, RCPs), and climate change will have the greatest impact on NH3 volatilization in the Yangtze river agro‐region of China due to high warming effects. However, the potential increase in NH3 volatilization under future climate change can be mitigated by 26.1−47.5% through various N fertilizer management optimization options. Abstract : A nonlinear model was established to predict NH3 volatilization from farmland in China. Future climate change will increase national NH3 emissions by 23.1–32.0% in 2050. Improved N fertilization could offset only 26.1–47.5% of the increase in NH3 emissions by climate change. … (more)
- Is Part Of:
- Global change biology. Volume 27:Number 24(2021)
- Journal:
- Global change biology
- Issue:
- Volume 27:Number 24(2021)
- Issue Display:
- Volume 27, Issue 24 (2021)
- Year:
- 2021
- Volume:
- 27
- Issue:
- 24
- Issue Sort Value:
- 2021-0027-0024-0000
- Page Start:
- 6525
- Page End:
- 6535
- Publication Date:
- 2021-09-12
- Subjects:
- cereal -- climate change scenario -- machine learning -- mineral nitrogen fertilizer -- NH3 volatilization -- nonlinear model
Climatic changes -- Environmental aspects -- Periodicals
Troposphere -- Environmental aspects -- Periodicals
Biodiversity conservation -- Periodicals
Eutrophication -- Periodicals
551.5 - Journal URLs:
- http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=gcb ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/gcb.15874 ↗
- Languages:
- English
- ISSNs:
- 1354-1013
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 4195.358330
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